Machine Learning and Deep Learning Training

Catalogue

Artificial Intelligence

Machine Learning and Deep Learning

Dive deep into the world of AI with a comprehensive training course covering Machine Learning and Deep Learning.

Grasp core concepts, methodologies, and the practical application of algorithms to decode complex datasets.

What will you learn?

Enhance your skills with our Machine Learning and Deep Learning course, covering:

Foundational principles of AI and Machine Learning.
Comprehensive study on Regression, Classification, and Clustering.
Advanced modules on Deep Learning and Neural Networks.
Hands-on labs using R for real-world case studies.

After completing the course, participants will:

Understand the core concepts of Machine Learning and Deep Learning.
Be proficient in applying various ML algorithms.
Gain insights into Regression Analysis and its types.
Familiarize with Classification methods, including SVM.
Explore the foundations and advanced aspects of Deep Learning.
Harness the power of R for data analysis.

Requirements:

Basic knowledge of statistical concepts.

Course Outline*:

*We know each team has their own needs and specifications. That is why we can modify the training outline per need.

1. Introduction to Machine Learning:

AI Emphasis & Applications
Supervised vs. Unsupervised Learning

2. Machine Learning Algorithms:

Regression Analysis

Simple & Multiple Regression
Estimation, Post-Estimation, and Model Accuracy
Resampling Methods: Cross-Validation, Bootstrap
Model Selection & Regularization: Subset Selection, Shrinkage Methods, Dimension Reduction

Classification

Logistic Regression & Predictions
Linear & Quadratic Discriminant Analysis
K-Nearest Neighbors, Support Vector Machines
Performance Evaluation: Sensitivity, ROC curve, and more

3. Introduction to Deep Learning:

Understanding ANN & Its Structure
Model Representation, Activation Functions
Back Propagation Algorithm and its Applications

4. Advanced Deep Learning:

The Nexusbetween AI & Deep Learning
Softmax Regression, Self-Taught Learning
Delving into Deep Networks
Demos and Applications

5. Lab Session:

Getting Started with R

Basic Commands, Data Manipulation, Import/Export
Graphical & Numerical Summaries, Writing Functions

Regression in R: Interaction Terms, Dummy Variables
Classification in R: Logistic Regression, LDA, QDA, KNN
Advanced Techniques: Resampling, Regularization, Support Vector Machine

Hands-on learning with expert instructors at your location for organizations.

Level:

Intermediate

Duration:

Hours (days:

)

Training customized to your needs

Immersive hands-on experience in a dedicated setting

*Price can range depending on number of participants, change of outline, location etc.

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Master new skills guided by experienced instructors from anywhere.

Level:

Intermediate

Duration:

Hours (days:

)

Training customized to your needs

Reduced training costs

*Price can range depending on number of participants, change of outline, location etc.

Get Quote

You can participate in a Public Course with people from other organisations.

/per trainee

Thanks for the numbers, they could be going to your emails. But they're going to mine... Thanks ;D

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Level:

Intermediate

Duration:

Hours (days:

)

Fits ideally for individuals and small groups

Networking opportunities with fellow participants.

*Price can range depending on number of participants, change of outline, location etc.

Get Quote

Machine Learning and Deep Learning

What will you learn?

Requirements:

Course Outline*:

1. Introduction to Machine Learning:

2. Machine Learning Algorithms:

3. Introduction to Deep Learning:

4. Advanced Deep Learning:

5. Lab Session:

Get Quote for:

Machine Learning and Deep Learning

Start your training experience here!